Here is my beginner's question:
We want to interface an existing C++ subroutine to R. The subroutine can be wrapped up in a C++ program, compiled with standard gcc, and run e.g. under GNU/Linux 2.6.18-128.1.14.el5. It accepts several arguments to it. (i) Using the .Call interface (with SEXP types) seems the best option since we want to pass matrices, vectors, scalars to it from R. However, the existing C++ subroutine is ~ hundreds of line long. To use Rcpp, it seems unavoidable (yet purpose-defeating) to have to make a lot of changes at the lower C++ level to be able to pass and handle these SEXP types. Is this correct or is there something we missed? (ii) From the convolution example (see slide #43/112 from Dirk's recent talk "Seamless R Extensions using Rcpp and RInside" at UCLA on March 30th), it is necessary to replace the std::vector in C++ to an object of type RcppVector<double>. Do other containers in C++ (set, list, map etc.) present in the original C++ code need to be replaced whenever they appear in the code, or is it just the containers which appear as arguments in the function call? (iii) When including Rcpp.h and building a shared object, can problems arise if the version of the gcc compiler used to build the shared object is different from the gcc compiler version that was used to generate the binary for R from the source code? Thanks Johnny
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